尝试：

  dt [，c（date_new = paste （date，collapse =;），。SD），by = id] 
 

I have a large data table of patient data. I want to delete rows where "id" is duplicated without losing the information in the "date" column.

id  date
01  2004-07-01
02  NA
03  2013-11-15
03  2005-03-15
04  NA
05  2011-07-01
05  2012-07-01

I could do this one of two ways -

1. create a column that writes over the date column values to concatenate all the dates for that ID, i.e.:

   id  date_new
   01  2004-07-01
   02  NA
   03  2013-11-15; 2005-03-15
   04  NA
   05  2011-07-01; 2012-07-01
   

or

2. create one new column for each additional date, i.e.:

   id  date_new    date_new2
   01  2004-07-01  NA
   02  NA          NA
   03  2013-11-15  2005-03-15
   04  NA          NA
   05  2011-07-01  2012-07-01
   

I have tried a few things, but they keep crashing my R session (I get the message R Session Aborted. R encountered a fatal error. The session was terminated.):

setkey(DT, "id")
unique_DT <- subset(unique(DT))

and:

DT[!duplicated(DT[, "id", with = FALSE])]

However, besides crashing R, neither of these solutions does what I want with the dates.

Any ideas? I am new to data table (and R generally) but I have the vague sense that I could solve this with := somehow.

Try this:

dt[,c(date_new=paste(date,collapse="; "),.SD),by=id]